Note: Descriptions are shown in the official language in which they were submitted.
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MASS SPECTROMETRY METHODS FOR CARCINOMA ASSESSMENTS
[0001] All patents, patent applications, and publications cited herein are
hereby
incorporated by reference in their entirety. The disclosures of these
publications in their
entireties are hereby incorporated by reference into this application in order
to more fully
describe the state of the art as known to those skilled therein as of the date
of the invention
described and claimed herein.
[0002] This patent disclosure contains material that is subject to
copyright protection. The
copyright owner has no objection to the facsimile reproduction by anyone of
the patent
document or the patent disclosure as it appears in the U.S. Patent and
Trademark Office
patent file or records, but otherwise reserves any and all copyright rights.
FIELD OF THE INVENTION
[0003] The present invention is directed to methods for identifying and
differentiating
squamous cell carcinomas, basal cell carcinomas, verrucas, and seborrheic
keratosis using
MALDI imaging mass spectrometry methods. The present invention is further
directed to
methods for identifying and differentiating manifestations of autoimmune
disorders (such as
psoriasis, rheumatoid arthritis, and the like) from cancers associated with
tissues where such
autoimmune disorders materialize, via using MALDI imaging mass spectrometry
methods.
BACKGROUND OF THE INVENTION
[0004] Carcinoma is a type of cancer that arises from cells that comprise
the skin or the
tissue lining organs, such as the liver or kidneys. Some common types of
carcinoma include,
but are not limited to, basal cell carcinoma, squamous cell carcinoma, renal
cell carcinoma,
ductal carcinoma in situ, invasive ductal carcinoma, and adenocarcinoma.
[0005] An autoimmune disorder is a condition wherein an immune response is
mounted
against the subject's own cells resulting in the subject's immune system
attacking its very
own tissue. Non-limiting examples of an autoimmune disorder include psoriasis,
psoriatic
arthritis, Crohn's disease, rheumatoid arthritis.
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SUMMARY OF THE INVENTION
[0006] An aspect of the invention is directed to methods of distinguishing
a squamous
lesion. In one embodiment, the method comprises subjecting a sample from a
subject to mass
spectrometry; obtaining a mass spectrometric profile from said sample;
comparing the sample
mass spectrometric profile to a profile obtained from a known normal sample, a
tissue
abnormality sample, and/or carcinoma sample; and identifying the lesion as a
carcinoma or
tissue abnormality based on the comparison between the mass spectrometric
profile and the
known profile or profiles. In one embodiment, the sample is a skin lesion
sample or
gastrointestinal lesion sample. In another embodiment, the tissue abnormality
is Seborrheic
Keratosis or Verruca Vulgaris. In a further embodiment, the carcinoma is basal
cell
carcinoma, squamous cell carcinoma, renal cell carcinoma, ductal carcinoma in
situ, invasive
ductal carcinoma, or adenocarcinoma.
[0007] An aspect of the invention is directed to methods of identifying
carcinoma or a
tissue abnormality. In one embodiment, the method comprises subjecting a
sample from a
subject to mass spectrometry; obtaining a mass spectrometric profile from the
sample;
comparing the sample mass spectrometric profile to a profile obtained from a
known normal,
a tissue abnormality, and/or carcinoma sample; and identifying said lesion as
a carcinoma or
tissue abnormality based on the comparison between said mass spectrometric
profile and said
known profile or profiles. In one embodiment, the sample is a skin lesion
sample or
gastrointestinal lesion sample. In another embodiment, the tissue abnormality
is Seborrheic
Keratosis or Verruca Vulgaris. In a further embodiment, the carcinoma is basal
cell
carcinoma, squamous cell carcinoma, renal cell carcinoma, ductal carcinoma in
situ, invasive
ductal carcinoma, or adenocarcinoma.
[0008] Another aspect of the invention is directed to at least one
biomarker for the
identification of carcinoma, T-cell lymphoma, tissue abnormalities, or a
combination thereof
in a tissue sample from a subject. In embodiments, the biomarker comprises a
molecular
signature obtained via mass spectrometry. The molecular signature can comprise
one or more
m/z peaks that are selectively present in carcinoma tissue. The molecular
signature can
comprise one or more peaks that are selectively present in any of various
tissue abnormalities
including, but not limited to Seborrheic Keratosis, Verruca Vulgaris,
psoriasis, psoriatic
arthritis, Crohn's disease, rheumatoid arthritis, or a combination thereof
[0009] An additional aspect of the invention is directed to a diagnostic
kit for identifying a
tissue as normal, a carcinoma, T-cell lymphoma, a tissue abnormality, or a
combination
thereof. In embodiments, the kit includes the biomarkers listed or otherwise
referenced herein
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and a means for measuring one or a combination of molecular profiles in a
tissue sample. In
an embodiment, the means for measuring one or a combination of molecular
profiles
comprises mass spectrometry.
[0010] Other objects and advantages of this invention will become readily
apparent from
the ensuing description.
BRIEF DESCRIPTION OF THE FIGURES
[0011] FIG. 1 shows a photograph of a hematoxylin and eosin (H&E)-stained
cutaneous
squamous lesion.
[0012] FIG. 2 shows imaging mass spectrometry. The diagnostic platform built
around
imaging mass spectrometry consists of 3 components: 1) a novel collaborative
web interface
that controls 2) a mass spectrometer, and 3) a data analysis pipeline for
classification of the
histology-directed mass spectral data.
[0013] FIG. 3 depicts the applications that the imaging mass spectrometry
platform can be
used with respect to gastrointestinal disorders.
[0014] FIG. 4 depicts the applications that the imaging mass spectrometry
platform can be
used with respect to bone/muscle disorders.
[0015] FIG. 5 depicts the applications that the imaging mass spectrometry
platform can be
used with respect to skin disorders/diseases and wound healing.
[0016] FIG. 6 is a diagram of the histology-directed MALDI Mass spectrometry
process.
[0017] FIG. 7 is a schematic of the histology-directed MALDI Mass spectrometry
process.
[0018] FIG. 8 shows the Pathology Interface for Mass Spectrometry (PIMS). Web
based
interface allows pathologists to guide mass spectrometry-based assays and
remotely
collaborate.
[0019] FIG. 9 shows the Pathology Interface for Mass Spectrometry (PIMS).
[0020] FIG. 10 shows the Pathology Interface for Mass Spectrometry (PIMS).
[0021] FIG. 11 shows the Pathology Interface for Mass Spectrometry (PIMS).
[0022] FIG. 12 is a diagram of the histology-directed MALDI Mass spectrometry
process.
[0023] FIG. 13 is a schematic of the histology-directed MALDI Mass
spectrometry
process.
[0024] FIG. 14 is a diagram of the histology-directed MALDI Mass spectrometry
process.
[0025] FIG. 15 is a diagram of the general data analysis workflow for the
histology-
directed MALDI Mass spectrometry process. After the spatially targeted MALDI-
MS data is
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acquired, machine learning algorithms are applied to mathematically model the
important
class-wise variation. Once these models are constructed from well-
characterized training
data, they can be applied to previously unknown data and classify it into one
of the original
classes. Importantly, while model building can sometimes be time consuming for
very large
data sets (hours to days), classification generally can be done in less than a
second, delivering
very rapid results after data acquisition.
[0026] FIG. 16 shows a study design with data obtained from 130 patient
samples. BCC:
Basal cell carcinoma; SCC: squamous cell carcinoma; SK: Seborrheic Keratosis;
VV:
Verruca Vulgaris.
[0027] FIG. 17 shows a study design with data obtained from 130 patient
samples. BCC:
Basal cell carcinoma; SCC: squamous cell carcinoma; SK: Seborrheic Keratosis;
VV:
Verruca Vulgaris.
[0028] FIG. 18 shows test set results as a majority per patient.
[0029] FIG. 19 shows test set results as mass spectra classification.
[0030] FIG. 20 shows H&E sections for Verruca Vulgaris (left panels),
Seborrheic
Keratosis (middle panels), and squamous cell carcinoma (right panels). Basal
cell carcinoma
is noted in blue while squamous cell carcinoma is noted in yellow. Each spot
is 300 p.m.
[0031] FIG. 21 shows H&E sections for Seborrheic Keratosis classified as
basal cell
carcinoma. Each spot is 300 p.m.
[0032] FIG. 22 shows light microscopy and fluorescent microscopy images.
[0033] FIG. 23 shows a protein identification plan.
[0034] FIG. 24 shows a graph of an unsupervised analysis: lesions in
molecular space.
Point = one mass spectrum. Structure of data shows separation of classes. Can
further probe
this molecular space to build a classifier capable of sorting new data.
[0035] FIG. 25 shows results from a supervised analysis, allowing for
pursuit of a
molecular diagnosis.
[0036] FIG. 26 shows H&E sections for Verruca Vulgaris (left panels), squamous
cell
carcinoma (middle panels), and Seborrheic Keratosis (right panels). Basal cell
carcinoma is
noted in blue while squamous cell carcinoma is noted in yellow. Each spot is
300 p.m.
[0037] FIG. 27 shows H&E sections for Verruca Vulgaris (top left panel),
squamous cell
carcinoma (bottom left panel), Basal cell carcinoma (top right panel), and
Seborrheic
Keratosis (bottom right panel). Each spot is 300 p.m.
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[0038] FIG. 28 shows H&E sections for Verruca Vulgaris (top left panel),
squamous cell
carcinoma (bottom left panel), Basal cell carcinoma (top right panel), and
Seborrheic
Keratosis (bottom right panel). Each spot is 300 p.m.
[0039] FIG. 29 shows H&E sections for Seborrheic Keratosis classified as
basal cell
carcinoma. Each spot is 300 p.m.
[0040] FIG. 30 shows H&E sections for Seborrheic Keratosis classified as
basal cell
carcinoma. Each spot is 300 p.m.
DETAILED DESCRIPTION OF THE INVENTION
Abbreviations and Definitions
[0041] Detailed descriptions of one or more preferred embodiments are
provided herein. It
is to be understood, however, that the present invention may be embodied in
various forms.
Therefore, specific details disclosed herein are not to be interpreted as
limiting, but rather as a
basis for the claims and as a representative basis for teaching one skilled in
the art to employ
the present invention in any appropriate manner.
[0042] The singular forms "a", "an" and "the" include plural reference
unless the context
clearly dictates otherwise. The use of the word "a" or "an" when used in
conjunction with the
term "comprising" in the claims and/or the specification may mean "one," but
it is also
consistent with the meaning of "one or more," "at least one," and "one or more
than one."
[0043] Wherever any of the phrases "for example," "such as," "including"
and the like are
used herein, the phrase "and without limitation" is understood to follow
unless explicitly
stated otherwise. Similarly "an example," "exemplary" and the like are
understood to be
nonlimiting.
[0044] The term "substantially" allows for deviations from the descriptor
that do not
negatively impact the intended purpose. Descriptive terms are understood to be
modified by
the term "substantially" even if the word "substantially" is not explicitly
recited. Therefore,
for example, the phrase "wherein the lever extends vertically" means "wherein
the lever
extends substantially vertically" so long as a precise vertical arrangement is
not necessary for
the lever to perform its function.
[0045] The terms "comprising" and "including" and "having" and "involving"
(and
similarly "comprises", "includes," "has," and "involves") and the like are
used
interchangeably and have the same meaning. Specifically, each of the terms is
defined
consistent with the common United States patent law definition of "comprising"
and is
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therefore interpreted to be an open term meaning "at least the following," and
is also
interpreted not to exclude additional features, limitations, aspects, etc.
Thus, for example, "a
process involving steps a, b, and c" means that the process includes at least
steps a, b and c.
Wherever the terms "a" or "an" are used, "one or more" is understood, unless
such
interpretation is nonsensical in context.
[0046] As used herein the term "about" is used herein to mean
approximately, roughly,
around, or in the region of When the term "about" is used in conjunction with
a numerical
range, it modifies that range by extending the boundaries above and below the
numerical
values set forth. In general, the term "about" is used herein to modify a
numerical value
above and below the stated value by a variance of 20 percent up or down
(higher or lower).
Carcinoma
[0047] Carcinoma is a type of cancer that arises from cells that comprise
the skin or the
tissue lining organs, such as the liver or kidneys. Some common types of
carcinoma include,
but are not limited to, basal cell carcinoma, squamous cell carcinoma, renal
cell carcinoma,
ductal carcinoma in situ, invasive ductal carcinoma, and adenocarcinoma.
Autoimmune Disorder
[0048] An autoimmune disorder is a condition wherein an immune response is
mounted
against the subject's own cells resulting in the subject's immune system
attacking its very
own tissue. Non-limiting examples of an autoimmune disorder include psoriasis,
psoriatic
arthritis, Crohn's disease, rheumatoid arthritis.
Protein-Based Detection - Mass Spectrometry
[0049] By exploiting the intrinsic properties of mass and charge, mass
spectrometry (MS)
can be resolved and confidently identified a wide variety of complex
compounds, including
proteins. Traditional quantitative MS has used electrospray ionization (ESI)
followed by
tandem MS (MS/MS) (Chen et al., 2001; Zhong et al., 2001; Wu et al., 2000)
while newer
quantitative methods are being developed using matrix assisted laser
desorption/ionization
(MALDI) followed by time of flight (TOF) MS (Bucknall et al., 2002;
Mirgorodskaya et al.,
2000; Gobom et al., 2000). In accordance with the present invention, one can
generate mass
spectrometry profiles that are useful for grading carcinomas and predicting
carcinoma patient
survival, without regard for the identity of specific proteins.
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Electrospray Ionisation
[0050] ESI is a convenient ionization technique developed by Fenn and
colleagues (Fenn
et al., 1989) that is used to produce gaseous ions from highly polar, mostly
nonvolatile
biomolecules, including lipids. The sample is injected as a liquid at low flow
rates (1-10
pL/min) through a capillary tube to which a strong electric field is applied.
The field
generates additional charges to the liquid at the end of the capillary and
produces a fine spray
of highly charged droplets that are electrostatically attracted to the mass
spectrometer inlet.
The evaporation of the solvent from the surface of a droplet as it travels
through the
desolvation chamber increases its charge density substantially. When this
increase exceeds
the Rayleigh stability limit, ions are ejected and ready for MS analysis.
[0051] A typical conventional ESI source consists of a metal capillary of
typically 0.1-0.3
mm in diameter, with a tip held approximately 0.5 to 5 cm (but more usually 1
to 3 cm) away
from an electrically grounded circular interface having at its center the
sampling orifice, such
as described by Kabarle et al. (1993). A potential difference of between 1 to
5 kV (but more
typically 2 to 3 kV) is applied to the capillary by power supply to generate a
high electrostatic
field (106 to 107 V/m) at the capillary tip. A sample liquid carrying the
analyte to be
analyzed by the mass spectrometer is delivered to tip through an internal
passage from a
suitable source (such as from a chromatograph or directly from a sample
solution via a liquid
flow controller). By applying pressure to the sample in the capillary, the
liquid leaves the
capillary tip as small highly electrically charged droplets and further
undergoes desolvation
and breakdown to form single or multicharged gas phase ions in the form of an
ion beam. The
ions are then collected by the grounded (or negatively charged) interface
plate and led
through an orifice into an analyzer of the mass spectrometer. During this
operation, the
voltage applied to the capillary is held constant. Aspects of construction of
ESI sources are
described, for example, in U.S. Pat. Nos. 5,838,002; 5,788,166; 5,757,994; RE
35,413; and
5,986,258, which are incorporated herein by reference in their entireties.
Electrospray Ionisation Tandem Mass Spectrometry (ESI/MS/MS)
[0052] In ESI tandem mass spectrometry (ESI/MS/MS), one can simultaneously
analyze
both precursor ions and product ions, thereby monitoring a single precursor
product reaction
and producing (through selective reaction monitoring (SRM)) a signal only when
the desired
precursor ion is present. When the internal standard is a stable isotope-
labeled version of the
analyte, this is known as quantification by the stable isotope dilution
method. This approach
has been used to accurately measure pharmaceuticals (Zweigenbaum et al., 2000;
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Zweigenbaum et al., 1999) and bioactive peptides (Desiderio et al., 1996;
Lovelace et al.,
1991). Newer methods are performed on widely available MALDI-TOF instruments,
which
can resolve a wider mass range and have been used to quantify metabolites,
peptides, and
proteins. Larger molecules such as peptides can be quantified using unlabeled
homologous
peptides as long as their chemistry is similar to the analyte peptide (Duncan
et al., 1993;
Bucknall et al., 2002). Protein quantification has been achieved by
quantifying tryptic
peptides (Mirgorodskaya et al., 2000). Complex mixtures such as crude extracts
can be
analyzed, but in some instances sample clean up is required (Nelson et al.,
1994; Gobom et
al., 2000).
Secondary Ion Mass Spectrometry (SIMS)
[0053] Secondary ion mass spectrometry, or SIMS, is an analytical method
that uses
ionized particles emitted from a surface for mass spectroscopy at a
sensitivity of detection of
a few parts per billion. The sample surface is bombarded by primary energetic
particles, such
as electrons, ions (e.g., 0, Cs), neutrals or even photons, forcing atomic and
molecular
particles to be ejected from the surface, a process called sputtering. Since
some of these
sputtered particles carry a charge, a mass spectrometer can be used to measure
their mass and
charge. Continued sputtering permits measuring of the exposed elements as
material is
removed. This in turn permits one to construct elemental depth profiles.
Although the
majority of secondary ionized particles are electrons, it is the secondary
ions which are
detected and analyzed by the mass spectrometer in this method.
LD-MS and LDLPMS
[0054] Laser desorption mass spectrometry (LD-MS) involves the use of a
pulsed laser,
which induces desorption of sample material from a sample site¨effectively,
this means
vaporization of sample off of the sample substrate. This method is usually
only used in
conjunction with a mass spectrometer, and can be performed simultaneously with
ionization
if one uses the right laser radiation wavelength.
[0055] When coupled with Time-of-Flight (TOF) measurement, LD-MS is referred
to as
LDLPMS (Laser Desorption Laser Photoionization Mass Spectrometry). The LDLPMS
method of analysis gives instantaneous volatilization of the sample, and this
form of sample
fragmentation permits rapid analysis without any wet extraction chemistry. The
LDLPMS
instrumentation provides a profile of the species present while the retention
time is low and
the sample size is small. In LDLPMS, an impactor strip is loaded into a vacuum
chamber.
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The pulsed laser is fired upon a certain spot of the sample site, and species
present are
desorbed and ionized by the laser radiation. This ionization also causes the
molecules to
break up into smaller fragment-ions. The positive or negative ions made are
then accelerated
into the flight tube, being detected at the end by a microchannel plate
detector. Signal
intensity, or peak height, is measured as a function of travel time. The
applied voltage and
charge of the particular ion determines the kinetic energy, and the separation
of fragments is
due to different size causing different velocity. Each ion mass will thus have
a different
flight-time to the detector.
[0056] One can either form positive ions or negative ions for analysis.
Positive ions are
made from regular direct photoionization, but negative ion formation requires
a higher
powered laser and a secondary process to gain electrons. Most of the molecules
that come off
the sample site are neutrals, and thus can attract electrons based on their
electron affinity. The
negative ion formation process is less efficient than forming just positive
ions. The sample
constituents will also affect the outlook of a negative ion spectra.
[0057] Other advantages with the LDLPMS method include the possibility of
constructing
the system to give a quiet baseline of the spectra because one can prevent
coevolved neutrals
from entering the flight tube by operating the instrument in a linear mode.
Also, in
environmental analysis, the salts in the air and as deposits will not
interfere with the laser
desorption and ionization. This instrumentation also is very sensitive, known
to detect trace
levels in natural samples without any prior extraction preparations.
MALDI-TOF-MS
[0058] Since its inception and commercial availability, the versatility of
MALDI-TOF-MS
has been demonstrated convincingly by its extensive use for qualitative
analysis. For
example, MALDI-TOF-MS has been employed for the characterization of synthetic
polymers
(Marie et al., 2000; Wu et al., 1998). peptide and protein analysis
(Roepstorff et al., 2000;
Nguyen et al., 1995), DNA and oligonucleotide sequencing (Miketova et al.,
1997; Faulstich
et al., 1997; Bentzley et al., 1996), and the characterization of recombinant
proteins
(Kanazawa et al., 1999; Villanueva et al., 1999). Recently, applications of
MALDI-TOF-MS
have been extended to include the direct analysis of biological tissues and
single cell
organisms in order to characterize endogenous peptide and protein constituents
(Li et al.,
2000; Lynn et al., 1999; Stoeckli et al., 2001; Caprioli et al., 1997;
Chaurand et al., 1999;
Jespersen et al., 1999).
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[0059] The properties that make MALDI-TOF-MS a popular qualitative tool¨its
ability
to analyze molecules across an extensive mass range, high sensitivity, minimal
sample
preparation and rapid analysis times¨also make it a useful quantitative tool.
MALDI-TOF-
MS also allows non-volatile and thermally labile molecules to be analyzed with
relative ease.
Without being bound by theory, MALDI-TOF-MS can be useful for quantitative
analysis in
clinical settings, for toxicological screenings, as well as for environmental
analysis. In
addition, the application of MALDI-TOF-MS to the quantification of peptides
and proteins is
also useful. The ability to quantify intact proteins in biological tissue and
fluids presents a
particular challenge in the expanding area of proteomics and investigators
urgently require
methods to accurately measure the absolute quantity of proteins. While there
have been
reports of quantitative MALDI-TOF-MS applications, there are many problems
inherent to
the MALDI ionization process that have restricted its widespread use (Kazmaier
et al., 1998;
Horak et al., 2001; Gobom et al., 2000; Wang et al., 2000; Desiderio et al.,
2000). These
limitations primarily stem from factors such as the sample/matrix
heterogeneity, which can
contribute to the large variability in observed signal intensities for
analytes, the limited
dynamic range due to detector saturation, and difficulties associated with
coupling MALDI-
TOF-MS to on-line separation techniques such as liquid chromatography.
Combined, these
factors are thought to compromise the accuracy, precision, and utility with
which quantitative
determinations can be made.
[0060] Because of these difficulties, practical examples of quantitative
applications of
MALDI-TOF-MS have been limited. Most of the studies to date have focused on
the
quantification of low mass analytes, in particular, alkaloids or active
ingredients in
agricultural or food products (Wang et al., 1999; Jiang et al., 2000; Wang et
al., 2000; Yang
et al., 2000; Wittmann et al., 2001), whereas other studies have demonstrated
the potential of
MALDI-TOF-MS for the quantification of biologically relevant analytes such as
neuropeptides, proteins, antibiotics, or various metabolites in biological
tissue or fluid
(Muddiman et al., 1996; Nelson et al., 1994; Duncan et al., 1993; Gobom et
al., 2000; Wu et
al., 1997; Mirgorodskaya et al., 2000). In earlier work it was shown that
linear calibration
curves could be generated by MALDI-TOF-MS provided that an appropriate
internal
standard was employed (Duncan et al, 1993). This standard can "correct" for
both sample-to-
sample and shot-to-shot variability. Stable isotope labeled internal standards
(isotopomers)
give the best result.
[0061] With the marked improvement in resolution available on modern
commercial
instruments, primarily because of delayed extraction (Bahr et al., 1997;
Takach et al., 1997),
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the opportunity to extend quantitative work to other examples is now possible;
not only of
low mass analytes, but also biopolymers. Of particular interest is the
prospect of absolute
multi-component quantification in biological samples (e.g., proteomics
applications).
[0062] The properties of the matrix material used in the MALDI method are
critical. Only
a select group of compounds is useful for the selective desorption of proteins
and
polypeptides. A review of all the matrix materials available for peptides and
proteins shows
that there are certain characteristics the compounds must share to be
analytically useful.
Despite its importance, very little is known about what makes a matrix
material "successful"
for MALDI. The few materials that do work well are used heavily by all MALDI
practitioners and new molecules are constantly being evaluated as potential
matrix
candidates. With a few exceptions, most of the matrix materials used are solid
organic acids.
Liquid matrices have also been investigated, but are not used routinely.
Immunohistochemistry
[0063] Antibodies can be used in conjunction with both fresh-frozen and/or
formalin-
fixed, paraffin-embedded tissue blocks prepared for study by
immunohistochemistry (IHC).
The method of preparing tissue blocks from these specimens has been
successfully used in
previous IHC studies of various prognostic factors, and/or is well known to
those of skill in
the art (Brown et al., 1990; Abbondanzo et al., 1999; Allred et al., 1990).
[0064] The present invention can also employ immunohistochemistry. This
approach uses
antibodies to detect and quantify antigens in intact tissue samples. Thin
sections of tissue
specimens are collected onto microscope slides. Samples that have been
formalin-fixed and
paraffin embedded must be subjected to deparaffinization and antigen retrieval
protocols
prior to incubation with an antibody against the target protein of interest.
Deparaffinization is
accomplished by incubating the slides in xylene to remove the paraffin
followed by graded
ethanol and water to rehydrate the sections. Antigen retrieval is carried out
through
incubating the sections in buffer such as tris or citrate with heat which may
be introduced via
a pressure cooker or a microwave. Sections can then be stained with antibodies
using a direct
or indirect method.
[0065] The direct method is a one-step staining method and involves a
labeled antibody
(e.g. FITC-conjugated antiserum) reacting directly with the antigen in tissue
sections. While
this technique utilizes only one antibody and therefore is simple and rapid,
the sensitivity is
lower due to little signal amplification, such as with indirect methods, and
is less commonly
used than indirect methods.
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[0066] The indirect method involves an unlabeled primary antibody (first
layer) that binds
to the target antigen in the tissue and a labeled secondary antibody (second
layer) that reacts
with the primary antibody. As mentioned above, the secondary antibody must be
raised
against the IgG of the animal species in which the primary antibody has been
raised. This
method is more sensitive than direct detection strategies because of signal
amplification due
to the binding of several secondary antibodies to each primary antibody if the
secondary
antibody is conjugated to the fluorescent or enzyme reporter.
Mass Spectrometry Target Proteins
[0067] The present invention provides a protein-based classification of
carcinomas. This
classification is based on the identification of peaks for at least two
peptides, the expression
of which correlates with various disease states.
Mass Spectrometry Profile
[0068] In one embodiment, the invention provides for examination of mass
spectrometry
profiles of proteins from various regions of a skin sample. The sample
contains both
melanocytic and stromal components, and one can examine either or both of
these regions.
[0069] The classification model as described herein is based on a peptide
signature
comprising a number of peaks.
Classification Model
[0070] Spectral classification is achieved using any of various software or
processes
known by those of ordinary skill in the art. In one exemplary embodiment,
spectral
classification is achieved by using R language supplied by the GNU project
(available from
the Free Software Foundation, Boston, MA). In alternative embodiment, spectral
classification is achieved by using the ClinProTools statistics package
supplied by Bruker
Daltonics Inc. (Billerica, MA, USA). In embodiments, spectra are organized and
grouped
according to the patient sample from which they originate. All spectra
belonging to the same
diagnosis are loaded into the software as a class with 2 or more classes being
loaded for one
analysis. All spectra are subjected to preprocessing which includes baseline
subtraction, noise
level estimation, and normalization to total ion current. Peak boundaries for
integration and
analysis are manually determined by selection of the monoisotopic peak or
automatically by
selecting signals with signal-to-noise greater than 3. The peak data can then
be used to create
a classification model. In embodiments, the peak data are used to create a
classification
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model using an iterative cross-validation approach where the underlying model
algorithm is
empirically selected based on performance. Before model training under one
embodiment,
the data undergoes a 70/30 training/test split. 70% of the data is sent for
training using a
cross-validation approach. The remaining 30% is reserved to test the final
model after cross-
validation. The cross-validation approach further splits the whole of the
training data (70% of
the total data) into 70% training and 30% cross-validation. The 70% portion of
the data is
trained, and tested on the remaining 30%. This process is repeated with
different random
subsets of the data. The final model is chosen based on accuracy performance.
[0071] In an embodiment, the classification model is created using a
genetic algorithm.
Under one embodiment, a set of peaks are chosen and evaluated for their
ability to classify
spectra into their correct diagnosis. This set of peaks can then then be
crossed with another
set of peaks, similar to genetic reproduction and the offspring can be
evaluated for their
classification ability. Those sets that perform better than the parents can be
further crossed
with other sets to determine the most optimal set of peaks while those that
perform worse,
can be discarded. This crossing and evaluation can be carried out over 50
generations to
determine the best optimized set of peaks for diagnostic classification. In
certain
embodiments, the maximum number of peaks to be used is set to 15, but in some
embodiments the software can determine the optimal number to include in the
model. The
maximum number of peaks can be, for example, up to 50. In other embodiments, a
maximum
of 20 peaks are used. The number of peaks to be used can be, for example, 1,
2, 3, 4, 5, 6, 7,
8,9, 10, 11, 12, 13, 14, or 15.
[0072] Once a model has been optimized, it can be evaluated through cross-
validation.
One embodiment uses a leave-20%-out crossvalidation approach. In this
embodiment, a
subset of 20% of the data can be randomly selected to be left out and the
remaining 80% can
be used to build the classification model. The model can then be applied to
the 20% that were
originally left out and the accuracy of the classification can be determined.
This can be
carried out over 10 iterations with a different random 20% left out each time.
[0073] Once a model has been optimized through cross-validation, it can be
evaluated
using the withheld test set. In an exemplary model building phase, the test
set data is
randomly selected from the annotated data with constraints to avoid any
imbalance in the
number of data points from each sample group. The model then classifies the
test set, and the
accuracy of the model is determined by finding the number of true positives
and negatives
versus false positives and negatives.
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[0074] Once an optimized classification model has been established, it can
be applied to
new data in a validation mode, a classification mode, or a combination of
thereof In the
validation mode, data are organized and identified as to the group to which
they belong. The
software then classifies the data and evaluates the accuracy of the
classification reporting
percentages of spectra correctly classified.
[0075] The final classification model can be applied to new, unknown data
in a blinded
fashion. In this classification mode, the researcher and the software are
blinded as to the
diagnoses of the sample from which the data originated. The software
classifies the data into
the group that it best matches and reports a list of classification results
for each spectrum.
Someone with knowledge of the clinical diagnosis of the samples must then
evaluate the
classification results as compared to the known diagnosis.
Carcinoma Therapies
[0076] Based on the stage of the cancer and other factors, treatment
options comprise
surgery, immunotherapy, targeted therapy, chemotherapy, or radiation therapy.
[0077] Generally, early stage cancer can be treated with surgery alone, but
more
advanced cancers often require other treatments, including multiple treatments
such as
adjuvant therapy.
[0078] Non-limiting examples of immunotherapies comprise interferon,
interleukin-2,
pembrolizumab, nivolumab, ipilimumab.
[0079] Non-limiting examples of targeted therapies comprise vemurafenib,
dabrafenib,
trametrinib, and codimetinib, imatinib, and nilotinib.
[0080] Non-limiting examples of chemotherapies comprise dacarbazine and
temozolomide.
Pharmaceutical Formulations and Routes of Administration
[0081] Where clinical applications are contemplated, it will be necessary
to prepare
pharmaceutical compositions in a form appropriate for the intended
application. Generally,
this will entail preparing compositions that are essentially free of pyrogens,
as well as other
impurities that could be harmful to humans or animals.
[0082] The phrase "pharmaceutically or pharmacologically acceptable" can
refer to
molecular entities and compositions that do not produce adverse, allergic, or
other untoward
reactions when administered to an animal or a human. As used herein,
"pharmaceutically
acceptable carrier" includes, for example, any and all solvents, dispersion
media, coatings,
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antibacterial and antifungal agents, isotonic and absorption delaying agents
and the like. The
use of such media and agents for pharmaceutically active substances is well
known in the art.
Supplementary active ingredients also can be incorporated into the
compositions.
[0083] Administration of these compositions for treatment of a subject in
need according
to the present invention will be via any common route so long as the target
tissue is available
via that route. This includes intradermal, subcutaneous, intramuscular,
intraperitoneal, or
intravenous injection. In particular, intratumoral routes and sites local and
regional to tumors
are contemplated. Such compositions would normally be administered as
pharmaceutically
acceptable compositions, described supra.
[0084] The active compounds also may be administered parenterally or
intraperitoneally.
Solutions of the active compounds as free base or pharmacologically acceptable
salts can be
prepared in water suitably mixed with a surfactant, such as
hydroxypropylcellulose.
Dispersions can also be prepared in glycerol, liquid polyethylene glycols, and
mixtures
thereof and in oils. Under ordinary conditions of storage and use, these
preparations contain a
preservative to prevent the growth of microorganisms.
[0085] The pharmaceutical forms suitable for injectable use include sterile
aqueous
solutions or dispersions and sterile powders for the extemporaneous
preparation of sterile
injectable solutions or dispersions. In all cases the form must be sterile and
must be fluid to
the extent that easy administration by a syringe is possible. It must be
stable under the
conditions of manufacture and storage and must be preserved against the
contaminating
action of microorganisms, such as bacteria and fungi. The carrier can be a
solvent or
dispersion medium containing, for example, water, ethanol, polyol (for
example, glycerol,
propylene glycol, and liquid polyethylene glycol, and the like), suitable
mixtures thereof, and
vegetable oils. The proper fluidity can be maintained, for example, by the use
of a coating,
such as lecithin, by the maintenance of the required particle size in the case
of dispersion and
by the use of surfactants. The prevention of the action of microorganisms can
be brought
about by various antibacterial and antifungal agents, for example, parabens,
chlorobutanol,
phenol, sorbic acid, thimerosal, and the like. In many cases, it will be
preferable to include
isotonic agents, for example, sugars or sodium chloride. Prolonged absorption
of the
injectable compositions can be brought about by the use in the compositions of
agents
delaying absorption, for example, aluminum monostearate and gelatin.
[0086] Sterile injectable solutions are prepared by incorporating the
active compounds in
the required amount in the appropriate solvent with various other ingredients
enumerated
above, as required, followed by filtered sterilization. Generally, dispersions
are prepared by
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incorporating the various sterilized active ingredients into a sterile vehicle
which contains the
basic dispersion medium and the required other ingredients from those
enumerated above. In
the case of sterile powders for the preparation of sterile injectable
solutions, the preferred
methods of preparation are vacuum-drying and freeze-drying techniques which
yield a
powder of the active ingredient plus any additional desired ingredient from a
previously
sterile-filtered solution thereof.
[0087] For oral administration the polypeptides of the present invention
may be
incorporated with excipients that may include water, binders, abrasives,
flavoring agents,
foaming agents, and humectants.
[0088] As used herein, "pharmaceutically acceptable carrier" includes any
and all
solvents, dispersion media, coatings, antibacterial and antifungal agents,
isotonic and
absorption delaying agents and the like. The use of such media and agents for
pharmaceutical
active substances is well known in the art. Except insofar as any conventional
media or agent
is incompatible with the active ingredient, its use in the therapeutic
compositions is
contemplated. Supplementary active ingredients can also be incorporated into
the
compositions.
[0089] The compositions of the present invention may be formulated in a
neutral or salt
form. Pharmaceutically-acceptable salts include the acid addition salts
(formed with the free
amino groups of the protein) and which are formed with inorganic acids such
as, for example,
hydrochloric or phosphoric acids, or such organic acids as acetic, oxalic,
tartaric, mandelic,
and the like. Salts formed with the free carboxyl groups can also be derived
from inorganic
bases such as, for example, sodium, potassium, ammonium, calcium, or ferric
hydroxides,
and such organic bases as isopropylamine, trimethylamine, histidine, procaine
and the like.
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EXAMPLES
[0090] Examples are provided below to facilitate a more complete
understanding of the
invention. The following examples illustrate the exemplary modes of making and
practicing
the invention. However, the scope of the invention is not limited to specific
embodiments
disclosed in these Examples, which are for purposes of illustration only,
since alternative
methods can be utilized to obtain similar results.
EXAMPLE 1
[0091] MALDI Imaging Mass Spectrometry Differentiates Squamous Cell
Carcinomas,
Basal Cell Carcinomas, Verrucas, and Seborrheic Keratoses
[0092] Cutaneous squamous lesions can be difficult to distinguish from
squamous cell
carcinoma, irritated verruca, irritated seborrheic keratosis, or an irritated,
squamatized basal
cell carcinoma. Reactive atypia or sampling issues can also present problems.
[0093] MALDI IMS is a powerful new technology for differentiating Squamous
Cell
Carcinomas, Basal Cell Carcinomas, Verrucae, and Seborrheic Keratoses.
[0094] Our technique unbiasedly differentiated the 4 lesion types with 96%
accuracy.
[0095] The algorithm developed and employed herein can further incorporate
known
clinical outcomes to assist in distinguishing borderline or ambiguous lesions.
The inventors
will characterize the peptides with substantial implication in lesion typing.
[0096] MS preprocessing: A large portion of the MALDI-MS data is unspecific
noise
which can influence the quality of the mathematical model (i.e. a model fits
to the noise and
not the important molecular data). To address this reality, in certain
embodiments, only the
peaks are selected from the data. In these embodiments, the dimensionality of
the data is
reduced (10s of thousands of features (m/zs)) to 100s of features which are
much more
compatible with machine learning. After extraction of the features (molecular
peaks), a table
of class vs peaks can be built. For each class there can be multiple
observations, and for each
observation, there can be hundreds of features.
[0097] Machine Learning: In the Example 1 study, once we acquired the
totality of the
data, we randomly split it into a training and a test set. The training set is
comprised of 75%
of the samples, while the test set is comprised of 25% of the samples. During
training, the test
set is COMPLETELY WITHHELD from the training set to prevent biasing our
classifier to
the data with which we will test it. For training, we cross validate on the
training set by
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randomly subset out 1/10 of the data, training a model, and iteratively repeat
this process 10
times (10x k-fold cross validation). From this procedure, we generate 100s of
models and we
select the one with the best self-cognition accuracy to apply to the test set.
Since all
classifications are known, we can determine the accuracy of our model on the
test set and get
a measure of how well it generalizes (i.e. how well it will perform in real
world setting),
although at a limited scale. The results are a table of unknown data and its
classification using
our model.
[0098]
EXAMPLE 2
[0099] Differentiating Mycosis Fungoides from Psoriasis: A MALDI Imaging
Mass
Spectrometry Approach
[00100] Mycosis fungoides is a common form of cutaneous T-cell lymphoma.
Traditionally difficult to diagnose, there is a great need for diagnostics to
aid in
differentiating from other diseases like psoriasis. Imaging mass spectrometry
(IMS) is an
analytical tool that provides molecular information from spatially defined
regions within
FFPE tissues. In dermatopathology, it has been successfully used to
differentiate melanoma
from melanocytic nevi. Here, we apply this new technology to differentiate
mycosis
fungoides from psoriasis. In this study, 20 patient samples of either mycosis
fungoides (10) or
psoriasis (10) were compared. 55 Spectra were collected from psoriasis and 59
from mycosis
fungoides samples. The method had an overall classification accuracy of 92.2%,
with 94.6%
accuracy in determining psoriasis and an 89.8% accuracy in determining mycosis
fungoides.
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EQUIVALENTS
[00101] Those skilled in the art will recognize, or be able to ascertain,
using no more than
routine experimentation, numerous equivalents to the specific substances and
procedures
described herein. Such equivalents are considered to be within the scope of
this invention,
and are covered by the following claims.
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